delivered by UCD, ATU Sligo and TU Dublin
The Data Science programme is for ICT professionals who wish to develop skills to support careers in Data Science and Data Engineering. Data Engineers design and build the infrastructure for data manipulation. While Data Scientists are experts in the Machine Learning and Analytics methods that derive insights from data. This programme offers a suite of modules on big data programming, machine learning, data analytics and AI presented by leading Data Science experts.
Introduction to probability and statistical inference, focusing on understanding concepts and methodologies.
Begineers introduction to the open-source statistical programming language R, and how to build programmes and handle datasets
Learn how to manipulate data and perform statistical analysis using Python.
The module uses a variety of real-world examples to illustrate the use of different data analytical techniques and regression models, covering both theoretical and practical considerations.
Introduction to computationally intensive modern Statistical methods, including concepts and methods involved in simulating from distributions using R.
This module/course delivers the basic techniques in Time Series Analysis. This course will mainly focus on examples in the world of economics and finance.
Learn about machine learning, Deep Learning and Convolutional Neural Networks for use in computer vision tasks
Gain expertise in interpreting linear algebra models used in the engineering literature to model problems
Learn about machine learning, Deep Learning & Convolutional Neural Networks for use in computer vision tasks
This course delivers a collection of techniques for discovering patterns in data and making predictions at the intersection of Machine Learning and Statistics.
This course will provide an introduction to Bayesian analysis with an emphasis on concepts in Bayesian theory and practice, focusing on statistical programming (Stan programming language).
This module will cover many common statistical techniques used to analyse high dimensional data (including: clustering techniques; classification techniques; ordination techniques; etc) using R software.
The module makes predictions from data with a focus on efficiency and optimization with respect to prediction accuracy, self-tuning and adaption (Follow on from STAT30270/STAT40750 modules).
This module explores the purposes of statistical inference and learning from data (what, how, why). Covering: probability, random variables, likelihoods, comparing methods and how to critically assess them.
This module covers advanced predictive analysis techniques including: linear regression, weighted least squares, ridge regression, mixed effects models, generalized linear models, amongst others.
Covers the essence of programming with data using the languages C and C++, focus on incorporating such code into the R statistical environment.
Focuses on how to manipulate data and perform statistical calculations using SAS.
Covers advanced use of R and Rstudio, following on from the Data Programming with R module.
Focuses on the analysis of relational data and reviews the available methodologies and algorithms that can be employed to model network interactions.
Covers the principles behind, and key characteristics, of stochastic models in real-world applications
Focuses on how to build complex models based on prior beliefs and how to use cutting edge computational methods
The Programme in Data Analytics will equip you with the skills necessary to understand and analyse large data sets. Techniquies applicable to ICT, pharma and financial services sectors amongst others.
This Masters Degree specialises in the design and development of Advanced Driver Assistance Systems, the underlaying technology of smart and autonomous vehicles. This part-time programme brings together interdisciplinary concepts such as computer vision, artificial intelligence, vehicle dynamics and advanced sensor systems to provide current engineers with the skills required to design the next generation of automotive technology.
The Programme in Data Analytics is at the crossroads between statistics and computer science, and contain elements of both. Students who perform well on the Professional Diploma may apply to transfer to online MSc Data Analytics.
ADAS and Autonomous System Architecture provides the learner with an appreciation for the bigger picture of the automotive industry. The student will gain an understanding of the multi-disciplinary nature of the industry, as well as knowledge of its supply chain. Different system architectures and design constraints are introduced.
This module investigates the physical and technical foundations, strengths and weaknesses of sensors for advanced driver assistance systems and their applications in environment detection in automotive vehicles
The founding industry Centre partners are:
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Learn from 3 of Ireland’s leading universities with world renowned academic staff.
Our courses and modules range from levels 6 to 9 on the NFQ framework.
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Select from 11 key themes across Digital Transformation.
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Our corporate network is innovative and expansive across many sectors.
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Choose from a range of online, on-campus and blended learning modes designed to suit your needs.
